Traffic accidents that cause the greatest damage occur during driving, and most of them are usually caused by drowsiness, DUI, and distraction.
As a method for preventing such traffic accidents in advance, a driver himself or herself had to be self-aware and careful, in the past. Recently, however, a driver state is monitored by using technology, and the driver is guided to safe driving by a warning, and a typical example thereof is a Driver-State Monitoring Device, hereinafter referred to as a DSM device.
The DSM device monitors the driver's face by projecting near infrared rays to the driver's face using a Near Infra-Red (NIR) camera and acquiring the driver's facial image accordingly. And an algorithm that assigns weights to factors closer to drowsiness by prioritizing the characteristics of blinking, such as the frequency of blinking, the number of times of blinking, is used to determine whether the driver is sleepy. In addition, a state of the distraction is determined by recognizing a facial direction and an ocular state, and the driver is warned in case the driver is determined as not looking at the front for a predetermined time.
However, in such conventional methods, there is a problem that the warning to the driver becomes meaningless when the driver is in a state of being unable to respond to the warning.
Further, in such conventional methods, when the driver's position is changed, there is a limit in detecting an abnormal state of the driver using the camera.
Accordingly, the inventors of the present disclosure propose a method to efficiently detect a hazardous state, such as a drowsiness state or an abnormal state, representing that the driver is asleep, etc. so as to prevent the traffic accidents in advance.